Optimal coordination of hydrogen-based integrated energy systems with combination of hydrogen and water storage

• Published in: Applied energy 2022-02, Vol.308, p.118274, Article 118274
• Main Authors: Dong, Xiangxiang, Wu, Jiang, Xu, Zhanbo, Liu, Kun, Guan, Xiaohong
• Format: Article
• Language: English
• Subjects: Coordination of integrated energy system; Demand side energy system; Energy storage; Hydrogen-based multi-energy system; Stochastic optimization
• ISSN: 0306-2619; 1872-9118
• DOI: 10.1016/j.apenergy.2021.118274

With the rapid development of hydrogen production and storage technologies, it is possible to develop a hydrogen-based integrated energy system (HIES) in demand side, which brings fundamental changes in the structure of energy and power systems. It is very important to optimally coordinate the HIES with the combination of hydrogen and water storage, which can handle the energy imbalance between the multi-energy supply and demand, thus improve the energy efficiency and make full use of renewable supply. To address this coordination problem with uncertainties in renewable supply and demand, a stochastic optimization problem is formulated and solved by a scenario-based algorithm to determine the operation strategy of the system. The performance of the developed method is analyzed based on a building energy system. Numerical results show that through the coordination of the hydrogen and water storage, 80% of energy cost saving can be achieved, since the system capability in response to changes in the price of electricity could be significantly enhanced, and the utilization efficiency of renewable supply could achieve 100%. Moreover, energy cost saving and carbon emission reduction could be simultaneously obtained, except for the cases with high hydrogen prices in the typical summer day. •A hydrogen-based integrated energy system with hydrogen and water tank is modeled.•The performance of hydrogen and water storage with renewable supply is analyzed.•A scenario-based algorithm is developed to efficiently handle system uncertainty.